Zellner, Hermann and Staudigel, Martin and Trenner, Thomas and Bittkowski, Meik and Wolowski, Vincent and Icking, Christian and Merkl, Rainer (2012) Prescont: Predicting protein-protein interfaces utilizing four residue properties. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 80 (1). pp. 154-168. ISSN 0887-3585, 1097-0134
Full text not available from this repository. (Request a copy)Abstract
An important task of computational biology is to identify those parts of a polypeptide chain, which are involved in interactions with other proteins. For this purpose, we have developed the program PresCont, which predicts in a robust manner amino acids that constitute protein-protein interfaces (PPIs). PresCont reaches state-of-the-art classification quality on the basis of only four residue properties that can be readily deduced from the 3D structure of an individual protein and a multiple sequence alignment (MSA) composed of homologs. The core of PresCont is a support vector machine, which assesses solvent-accessible surface area, hydrophobicity, conservation, and the local environment of each amino acid on the protein surface. For training and performance testing, we compiled three nonoverlapping datasets consisting of permanently formed or transient complexes, respectively. A comparison with SPPIDER, ProMate, and meta-PPISP showed that PresCont compares favorably with these highly sophisticated programs, and that its prediction quality is less dependent on the type of protein complex being considered. This balance is due to a mutual compensation of classification weaknesses observed for individual properties: For PPIs of permanent complexes, solvent-accessible surface and hydrophobicity contribute most to classification quality, for PPIs of transient complexes, the assessment of the local environment is most significant. Moreover, we show that for permanent complexes a segmentation of PPIs into core and rim residues has only a moderate influence on prediction quality. PresCont is available as a web service at . Proteins 2012; (C) 2011 Wiley Periodicals, Inc.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | INTERACTION-SITE PREDICTION; BINDING HOT-SPOTS; HYDROPHOBIC PATCHES; SECONDARY STRUCTURE; CONSERVATION; SEQUENCE; ACCURACY; IDENTIFICATION; RECOGNITION; FREQUENCIES; support vector machine; machine learning; protein complexes; residue classification |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Rainer Merkl |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 25 May 2020 12:02 |
| Last Modified: | 25 May 2020 12:02 |
| URI: | https://pred.uni-regensburg.de/id/eprint/19582 |
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